Evaluating Characteristics of De Novo Assembly Software on 454 Transcriptome Data: A Simulation Approach
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{"title"=>"Evaluating characteristics of de novo assembly software on 454 transcriptome data: A simulation approach", "type"=>"journal", "authors"=>[{"first_name"=>"Marvin", "last_name"=>"Mundry", "scopus_author_id"=>"6602556511"}, {"first_name"=>"Erich", "last_name"=>"Bornberg-Bauer", "scopus_author_id"=>"6603818279"}, {"first_name"=>"Michael", "last_name"=>"Sammeth", "scopus_author_id"=>"57193078807"}, {"first_name"=>"Philine G D", "last_name"=>"Feulner", "scopus_author_id"=>"8430413700"}], "year"=>2012, "source"=>"PLoS ONE", "identifiers"=>{"sgr"=>"84857529522", "doi"=>"10.1371/journal.pone.0031410", "pui"=>"364349957", "pmid"=>"22384018", "scopus"=>"2-s2.0-84857529522", "issn"=>"19326203", "isbn"=>"1932-6203"}, "id"=>"901a1bf8-5127-3f54-bcd4-a2460f1739eb", "abstract"=>"BACKGROUND: The quantity of transcriptome data is rapidly increasing for non-model organisms. As sequencing technology advances, focus shifts towards solving bioinformatic challenges, of which sequence read assembly is the first task. Recent studies have compared the performance of different software to establish a best practice for transcriptome assembly. Here, we adapted a simulation approach to evaluate specific features of assembly programs on 454 data. The novelty of our study is that the simulation allows us to calculate a model assembly as reference point for comparison.\\n\\nFINDINGS: The simulation approach allows us to compare basic metrics of assemblies computed by different software applications (CAP3, MIRA, Newbler, and Oases) to a known optimal solution. We found MIRA and CAP3 are conservative in merging reads. This resulted in comparably high number of short contigs. In contrast, Newbler more readily merged reads into longer contigs, while Oases produced the overall shortest assembly. Due to the simulation approach, reads could be traced back to their correct placement within the transcriptome. Together with mapping reads onto the assembled contigs, we were able to evaluate ambiguity in the assemblies. This analysis further supported the conservative nature of MIRA and CAP3, which resulted in low proportions of chimeric contigs, but high redundancy. Newbler produced less redundancy, but the proportion of chimeric contigs was higher.\\n\\nCONCLUSION: Our evaluation of four assemblers suggested that MIRA and Newbler slightly outperformed the other programs, while showing contrasting characteristics. Oases did not perform very well on the 454 reads. Our evaluation indicated that the software was either conservative (MIRA) or liberal (Newbler) about merging reads into contigs. This suggested that in choosing an assembly program researchers should carefully consider their follow up analysis and consequences of the chosen approach to gain an assembly.", "link"=>"http://www.mendeley.com/research/evaluating-characteristics-novo-assembly-software-454-transcriptome-data-simulation-approach", "reader_count"=>162, "reader_count_by_academic_status"=>{"Unspecified"=>1, "Professor > Associate Professor"=>16, "Researcher"=>44, "Student > Doctoral Student"=>10, "Student > Ph. D. Student"=>51, "Student > Postgraduate"=>8, "Student > Master"=>13, "Other"=>3, "Student > Bachelor"=>6, "Lecturer"=>2, "Lecturer > Senior Lecturer"=>2, "Professor"=>6}, "reader_count_by_user_role"=>{"Unspecified"=>1, "Professor > Associate Professor"=>16, "Researcher"=>44, "Student > Doctoral Student"=>10, "Student > Ph. D. Student"=>51, "Student > Postgraduate"=>8, "Student > Master"=>13, "Other"=>3, "Student > Bachelor"=>6, "Lecturer"=>2, "Lecturer > Senior Lecturer"=>2, "Professor"=>6}, "reader_count_by_subject_area"=>{"Unspecified"=>3, "Engineering"=>2, "Biochemistry, Genetics and Molecular Biology"=>14, "Agricultural and Biological Sciences"=>126, "Medicine and Dentistry"=>4, "Business, Management and Accounting"=>1, "Chemistry"=>1, "Social Sciences"=>1, "Computer Science"=>8, "Immunology and Microbiology"=>1, "Earth and Planetary Sciences"=>1}, "reader_count_by_subdiscipline"=>{"Engineering"=>{"Engineering"=>2}, "Medicine and Dentistry"=>{"Medicine and Dentistry"=>4}, "Chemistry"=>{"Chemistry"=>1}, "Social Sciences"=>{"Social Sciences"=>1}, "Immunology and Microbiology"=>{"Immunology and Microbiology"=>1}, "Earth and Planetary Sciences"=>{"Earth and Planetary Sciences"=>1}, "Agricultural and Biological Sciences"=>{"Agricultural and Biological Sciences"=>126}, "Computer Science"=>{"Computer Science"=>8}, "Business, Management and Accounting"=>{"Business, Management and Accounting"=>1}, "Biochemistry, Genetics and Molecular Biology"=>{"Biochemistry, Genetics and Molecular Biology"=>14}, "Unspecified"=>{"Unspecified"=>3}}, "reader_count_by_country"=>{"Romania"=>1, "United States"=>4, "Japan"=>1, "United Kingdom"=>1, "Paraguay"=>1, "Spain"=>1, "India"=>1, "Canada"=>1, "Austria"=>1, "Sweden"=>2, "Norway"=>1, "Brazil"=>3, "Mexico"=>1, "Italy"=>1, "Slovenia"=>1, "Israel"=>1, "France"=>3, "Australia"=>1, "Chile"=>1, "Germany"=>5}, "group_count"=>3}

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  • {"files"=>["https://ndownloader.figshare.com/files/674438"], "description"=>"<p>Counts of contigs longer than 200, 400, 800, and 1000 base pairs for the different assemblies. Assemblies of simulated (top) and real 454 reads (bottom) are shown in separate diagrams.</p>", "links"=>[], "tags"=>["contig", "lengths"], "article_id"=>344926, "categories"=>["Information And Computing Sciences", "Biological Sciences", "Genetics"], "users"=>["Marvin Mundry", "Erich Bornberg-Bauer", "Michael Sammeth", "Philine G. D. Feulner"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0031410.g002", "stats"=>{"downloads"=>1, "page_views"=>3, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Cumulative_contig_lengths_for_different_assemblies_/344926", "title"=>"Cumulative contig lengths for different assemblies.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2013-02-20 08:19:55"}
  • {"files"=>["https://ndownloader.figshare.com/files/674549"], "description"=>"<p>AS: Genes with alternative splicing.</p><p>Non-AS: Genes without alternative splicing.</p>", "links"=>[], "tags"=>["chimera"], "article_id"=>345041, "categories"=>["Information And Computing Sciences", "Biological Sciences", "Genetics"], "users"=>["Marvin Mundry", "Erich Bornberg-Bauer", "Michael Sammeth", "Philine G. D. Feulner"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0031410.t008", "stats"=>{"downloads"=>0, "page_views"=>1, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Evaluation_of_chimera_formation_/345041", "title"=>"Evaluation of chimera formation.", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2013-02-20 08:20:29"}
  • {"files"=>["https://ndownloader.figshare.com/files/674584"], "description"=>"<p>*Utilising a wrapper TGICL <a href=\"http://www.plosone.org/article/info:doi/10.1371/journal.pone.0031410#pone.0031410-Pertea1\" target=\"_blank\">[33]</a> or est2assmbly <a href=\"http://www.plosone.org/article/info:doi/10.1371/journal.pone.0031410#pone.0031410-Papanicolaou1\" target=\"_blank\">[35]</a>.</p>§<p>For more studies refer to <a href=\"http://www.plosone.org/article/info:doi/10.1371/journal.pone.0031410#pone-0031410-t001\" target=\"_blank\">Table 1</a> in <a href=\"http://www.plosone.org/article/info:doi/10.1371/journal.pone.0031410#pone.0031410-Kumar1\" target=\"_blank\">[1]</a>.</p>", "links"=>[], "tags"=>["454", "transcriptome"], "article_id"=>345072, "categories"=>["Information And Computing Sciences", "Biological Sciences", "Genetics"], "users"=>["Marvin Mundry", "Erich Bornberg-Bauer", "Michael Sammeth", "Philine G. D. Feulner"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0031410.t001", "stats"=>{"downloads"=>7, "page_views"=>13, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Assembler_software_recently_used_for_de_novo_assembly_of_454_transcriptome_data_167_/345072", "title"=>"Assembler software recently used for <i>de novo</i> assembly of 454 transcriptome data.<sup>§</sup>", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2013-02-20 08:20:39"}
  • {"files"=>["https://ndownloader.figshare.com/files/674789"], "description"=>"<p>Comparison between simulated 454 read assemblies and model assembly.</p>", "links"=>[], "tags"=>["simulated", "454", "assemblies"], "article_id"=>345277, "categories"=>["Information And Computing Sciences", "Biological Sciences", "Genetics"], "users"=>["Marvin Mundry", "Erich Bornberg-Bauer", "Michael Sammeth", "Philine G. D. Feulner"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0031410.t006", "stats"=>{"downloads"=>1, "page_views"=>4, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Comparison_between_simulated_454_read_assemblies_and_model_assembly_/345277", "title"=>"Comparison between simulated 454 read assemblies and model assembly.", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2013-02-20 08:21:40"}
  • {"files"=>["https://ndownloader.figshare.com/files/674301"], "description"=>"<p>Workflows are shown in grey, comparisons between data sets in black. To evaluate the performance of different assemblers three comparisons were performed: 1) Different assemblies of simulated reads were compared to a Model Assembly (MA), which was based on positional information. 2) Different assemblies of simulated reads were compared to a transcriptome annotation. The MA was compared in the same way to provide reference values for the evaluated measurements. 3) Different assemblies of real reads were compared to the transcriptome annotation to compare the simulation approach to values from a real data set.</p>", "links"=>[], "tags"=>["assembler"], "article_id"=>344791, "categories"=>["Information And Computing Sciences", "Biological Sciences", "Genetics"], "users"=>["Marvin Mundry", "Erich Bornberg-Bauer", "Michael Sammeth", "Philine G. D. Feulner"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0031410.g001", "stats"=>{"downloads"=>1, "page_views"=>10, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Workflow_and_comparison_scheme_for_assembler_evaluation_/344791", "title"=>"Workflow and comparison scheme for assembler evaluation.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2013-02-20 08:19:10"}
  • {"files"=>["https://ndownloader.figshare.com/files/674647"], "description"=>"*<p>Only contigs >100 bp.</p>**<p>Summed time for velveth, velvetg, and Oases.</p>", "links"=>[], "tags"=>["metrics", "454"], "article_id"=>345144, "categories"=>["Information And Computing Sciences", "Biological Sciences", "Genetics"], "users"=>["Marvin Mundry", "Erich Bornberg-Bauer", "Michael Sammeth", "Philine G. D. Feulner"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0031410.t002", "stats"=>{"downloads"=>1, "page_views"=>6, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Basic_assembly_metrics_simulated_454_reads_/345144", "title"=>"Basic assembly metrics (simulated 454 reads).", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2013-02-20 08:20:59"}
  • {"files"=>["https://ndownloader.figshare.com/files/674717"], "description"=>"<p>Comparison between simulated 454 read assemblies and transcriptome.</p>", "links"=>[], "tags"=>["simulated", "454", "assemblies"], "article_id"=>345206, "categories"=>["Information And Computing Sciences", "Biological Sciences", "Genetics"], "users"=>["Marvin Mundry", "Erich Bornberg-Bauer", "Michael Sammeth", "Philine G. D. Feulner"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0031410.t004", "stats"=>{"downloads"=>1, "page_views"=>8, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Comparison_between_simulated_454_read_assemblies_and_transcriptome_/345206", "title"=>"Comparison between simulated 454 read assemblies and transcriptome.", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2013-02-20 08:21:19"}
  • {"files"=>["https://ndownloader.figshare.com/files/674685"], "description"=>"<p>Comparison between real 454 read assemblies and transcriptome.</p>", "links"=>[], "tags"=>["454", "assemblies"], "article_id"=>345174, "categories"=>["Information And Computing Sciences", "Biological Sciences", "Genetics"], "users"=>["Marvin Mundry", "Erich Bornberg-Bauer", "Michael Sammeth", "Philine G. D. Feulner"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0031410.t005", "stats"=>{"downloads"=>1, "page_views"=>1, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Comparison_between_real_454_read_assemblies_and_transcriptome_/345174", "title"=>"Comparison between real 454 read assemblies and transcriptome.", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2013-02-20 08:21:09"}
  • {"files"=>["https://ndownloader.figshare.com/files/674613"], "description"=>"<p>*Only contigs >100 bp.</p><p>**Summed time for velveth, velvetg, and Oases.</p>", "links"=>[], "tags"=>["metrics", "454"], "article_id"=>345106, "categories"=>["Information And Computing Sciences", "Biological Sciences", "Genetics"], "users"=>["Marvin Mundry", "Erich Bornberg-Bauer", "Michael Sammeth", "Philine G. D. Feulner"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0031410.t003", "stats"=>{"downloads"=>4, "page_views"=>5, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Basic_assembly_metrics_real_454_reads_/345106", "title"=>"Basic assembly metrics (real 454 reads).", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2013-02-20 08:20:49"}

PMC Usage Stats | Further Information

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Relative Metric

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